VIE-KET: Frames + Prolog. - Bernhard Pfahringer; Christian Holzbaur (ÖGAI, 1985)

A decision support system for village health workers in developing countries. - Bernhard Pfahringer; M. Hoberstorfer; Robert Trappl (Appl. Artif. Intell., 1988)

Extending Explanation-Based Generalization. - Bernhard Pfahringer (ÖGAI, 1989)

VIE-DU: Dialogue by Unification. - Ernst Buchberger; Elizabeth Garner; Wolfgang Heinz; Johannes Matiasek; Bernhard Pfahringer (ÖGAI, 1991)

The Logical Way to Build a DL-based KR System. - Bernhard Pfahringer (Description Logics, 1992)

Controlling Constructive Induction in CIPF: An MDL Approach. - Bernhard Pfahringer (ECML, 1994)

Robust Constructive Induction. - Bernhard Pfahringer (KI, 1994)

A New MDL Measure for Robust Rule Induction (Extended Abstract). - Bernhard Pfahringer (ECML, 1995)

Compression-Based Discretization of Continuous Attributes. - Bernhard Pfahringer (ICML, 1995)

Compression-Based Evaluation of Partial Determinations. - Bernhard Pfahringer; Stefan Kramer 001 (KDD, 1995)

Efficient Search for Strong Partial Determinations. - Stefan Kramer 001; Bernhard Pfahringer (KDD, 1996)

Compression-Based Pruning of Decision Lists. - Bernhard Pfahringer (ECML, 1997)

Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail. - Stefan Kramer 001; Bernhard Pfahringer; Christoph Helma (KDD, 1997)

Stochastic Propositionalization of Non-determinate Background Knowledge. - Stefan Kramer 001; Bernhard Pfahringer; Christoph Helma (ILP, 1998)

Guest Editorial: First-Order Knowledge Discovery in Databases. - Johannes Fürnkranz; Bernhard Pfahringer (Appl. Artif. Intell., 1998)

Learning to Use Operational Advice. - Johannes Fürnkranz; Bernhard Pfahringer; Hermann Kaindl; Stefan Kramer 001 (ECAI, 2000)

Meta-Learning by Landmarking Various Learning Algorithms. - Bernhard Pfahringer; Hilan Bensusan; Christophe G. Giraud-Carrier (ICML, 2000)

Searching for Patterns in Political Event Sequences: Experiments with the Keds Database. - Klaus Kovar; Johannes Fürnkranz; Johann Petrak; Bernhard Pfahringer; Robert Trappl; Gerhard Widmer (Cybern. Syst., 2000)

Winning the KDD99 Classification Cup: Bagged Boosting. - Bernhard Pfahringer (SIGKDD Explor., 2000)

Wrapping Boosters against Noise. - Bernhard Pfahringer; Geoffrey Holmes 001; Gabi Schmidberger (Australian Joint Conference on Artificial Intelligence, 2001)

Optimizing the Induction of Alternating Decision Trees. - Bernhard Pfahringer; Geoffrey Holmes 001; Richard Kirkby (PAKDD, 2001)

Prediction of Ordinal Classes Using Regression Trees. - Stefan Kramer 001; Gerhard Widmer; Bernhard Pfahringer; Michael de Groeve (Fundam. Informaticae, 2001)

Multiclass Alternating Decision Trees. - Geoffrey Holmes 001; Bernhard Pfahringer; Richard Kirkby; Eibe Frank; Mark Hall 002 (ECML, 2002)

Tabling Structures for Bottom-Up Logic Programming. - Roger Clayton; John G. Cleary; Bernhard Pfahringer; Mark Utting (LOPSTR, 2002)

A Two-Level Learning Method for Generalized Multi-instance Problems. - Nils Weidmann; Eibe Frank; Bernhard Pfahringer (ECML, 2003)

Text Categorisation Using Document Profiling. - Maximilien Sauban; Bernhard Pfahringer (PKDD, 2003)

Locally Weighted Naive Bayes. - Eibe Frank; Mark A. Hall; Bernhard Pfahringer (UAI, 2003)

Multinomial Naive Bayes for Text Categorization Revisited. - Ashraf M. Kibriya; Eibe Frank; Bernhard Pfahringer; Geoffrey Holmes 001 (Australian Conference on Artificial Intelligence, 2004)

Clustering Large Datasets Using Cobweb and K-Means in Tandem. - Mi Li; Geoffrey Holmes 001; Bernhard Pfahringer (Australian Conference on Artificial Intelligence, 2004)

A Toolbox for Learning from Relational Data with Propositional and Multi-instance Learners. - Peter Reutemann; Bernhard Pfahringer; Eibe Frank (Australian Conference on Artificial Intelligence, 2004)

Experiments In Predicting Biodegradability. - Hendrik Blockeel; Saso Dzeroski; Boris Kompare; Stefan Kramer 001; Bernhard Pfahringer; Wim Van Laer (Appl. Artif. Intell., 2004)

The Weka solution to the 2004 KDD Cup. - Bernhard Pfahringer (SIGKDD Explor., 2004)

WEKA - A Machine Learning Workbench for Data Mining. - Eibe Frank; Mark A. Hall; Geoffrey Holmes 001; Richard Kirkby; Bernhard Pfahringer (The Data Mining and Knowledge Discovery Handbook, 2005)

Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams. - Geoffrey Holmes 001; Bernhard Pfahringer; Richard Kirkby (CITA, 2005)

Stress-Testing Hoeffding Trees. - Geoffrey Holmes 001; Richard Kirkby; Bernhard Pfahringer (PKDD, 2005)

Using Weighted Nearest Neighbor to Benefit from Unlabeled Data. - Kurt Driessens; Peter Reutemann; Bernhard Pfahringer; Claire Leschi (PAKDD, 2006)

Improving on Bagging with Input Smearing. - Eibe Frank; Bernhard Pfahringer (PAKDD, 2006)

New Options for Hoeffding Trees. - Bernhard Pfahringer; Geoffrey Holmes 001; Richard Kirkby (Australian Conference on Artificial Intelligence, 2007)

Clustering Relational Data Based on Randomized Propositionalization. - Grant Anderson; Bernhard Pfahringer (ILP, 2007)

Scaling Up Semi-supervised Learning: An Efficient and Effective LLGC Variant. - Bernhard Pfahringer; Claire Leschi; Peter Reutemann (PAKDD, 2007)

Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis. - Stefan Mutter; Bernhard Pfahringer; Geoffrey Holmes 001 (Australasian Conference on Artificial Intelligence, 2008)

Mining Arbitrarily Large Datasets Using Heuristic k-Nearest Neighbour Search. - Xing Wu; Geoffrey Holmes 001; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2008)

Multi-label Classification Using Ensembles of Pruned Sets. - Jesse Read; Bernhard Pfahringer; Geoffrey Holmes 001 (ICDM, 2008)

Organizing the World's Machine Learning Information. - Joaquin Vanschoren; Hendrik Blockeel; Bernhard Pfahringer; Geoffrey Holmes 001 (ISoLA, 2008)

Exploiting Propositionalization Based on Random Relational Rules for Semi-supervised Learning. - Grant Anderson; Bernhard Pfahringer (PAKDD, 2008)

Handling Numeric Attributes in Hoeffding Trees. - Bernhard Pfahringer; Geoffrey Holmes 001; Richard Kirkby (PAKDD, 2008)

Learning from the Past with Experiment Databases. - Joaquin Vanschoren; Bernhard Pfahringer; Geoffrey Holmes 001 (PRICAI, 2008)

Improving Adaptive Bagging Methods for Evolving Data Streams. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer; Ricard Gavaldà (ACML, 2009)

The Positive Effects of Negative Information: Extending One-Class Classification Models in Binary Proteomic Sequence Classification. - Stefan Mutter; Bernhard Pfahringer; Geoffrey Holmes 001 (Australasian Conference on Artificial Intelligence, 2009)

Relational Random Forests Based on Random Relational Rules. - Grant Anderson; Bernhard Pfahringer (IJCAI, 2009)

New ensemble methods for evolving data streams. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer; Richard Kirkby; Ricard Gavaldà (KDD, 2009)

The WEKA data mining software: an update. - Mark Hall 002; Eibe Frank; Geoffrey Holmes 001; Bernhard Pfahringer; Peter Reutemann; Ian H. Witten (SIGKDD Explor., 2009)

Clustering Performance on Evolving Data Streams: Assessing Algorithms and Evaluation Measures within MOA. - Philipp Kranen; Hardy Kremer; Timm Jansen; Thomas Seidl 001; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer (ICDM Workshops, 2010)

Fast Perceptron Decision Tree Learning from Evolving Data Streams. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer; Eibe Frank (PAKDD (2), 2010)

Leveraging Bagging for Evolving Data Streams. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer (ECML/PKDD (1), 2010)

Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking. - Albert Bifet; Eibe Frank; Geoffrey Holmes 001; Bernhard Pfahringer (ACML, 2010)

MOA: Massive Online Analysis. - Albert Bifet; Geoff Holmes 001; Richard Kirkby; Bernhard Pfahringer (J. Mach. Learn. Res., 2010)

MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering. - Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer; Philipp Kranen; Hardy Kremer; Timm Jansen; Thomas Seidl 001 (WAPA, 2010)

WEKA - Experiences with a Java Open-Source Project. - Remco R. Bouckaert; Eibe Frank; Mark A. Hall; Geoffrey Holmes 001; Bernhard Pfahringer; Peter Reutemann; Ian H. Witten (J. Mach. Learn. Res., 2010)

Weka-A Machine Learning Workbench for Data Mining. - Eibe Frank; Mark Hall 002; Geoffrey Holmes 001; Richard Kirkby; Bernhard Pfahringer; Ian H. Witten; Len Trigg (Data Mining and Knowledge Discovery Handbook, 2010)

Conjunctive Normal Form. - Bernhard Pfahringer (Encyclopedia of Machine Learning, 2010)

Semi-random Model Tree Ensembles: An Effective and Scalable Regression Method. - Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2011)

Bagging Ensemble Selection. - Quan Sun; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2011)

Using the online cross-entropy method to learn relational policies for playing different games. - Samuel Sarjant; Bernhard Pfahringer; Kurt Driessens; Tony Smith (CIG, 2011)

MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer (Discovery Science, 2011)

Mining frequent closed graphs on evolving data streams. - Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer; Ricard Gavaldà (KDD, 2011)

An effective evaluation measure for clustering on evolving data streams. - Hardy Kremer; Philipp Kranen; Timm Jansen; Thomas Seidl 001; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer (KDD, 2011)

MOA: A Real-Time Analytics Open Source Framework. - Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer; Jesse Read; Philipp Kranen; Hardy Kremer; Timm Jansen; Thomas Seidl 001 (ECML/PKDD (3), 2011)

Active Learning with Evolving Streaming Data. - Indre Zliobaite; Albert Bifet; Bernhard Pfahringer; Geoff Holmes 001 (ECML/PKDD (3), 2011)

Detecting Sentiment Change in Twitter Streaming Data. - Albert Bifet; Geoffrey Holmes 001; Bernhard Pfahringer; Ricard Gavaldà (WAPA, 2011)

Streaming Multi-label Classification. - Jesse Read; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer (WAPA, 2011)

MOA Concept Drift Active Learning Strategies for Streaming Data. - Indre Zliobaite; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer (WAPA, 2011)

Classifier chains for multi-label classification. - Jesse Read; Bernhard Pfahringer; Geoff Holmes 001; Eibe Frank (Mach. Learn., 2011)

Bagging Ensemble Selection for Regression. - Quan Sun; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2012)

Stream Data Mining Using the MOA Framework. - Philipp Kranen; Hardy Kremer; Timm Jansen; Thomas Seidl 001; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer; Jesse Read (DASFAA (2), 2012)

Full model selection in the space of data mining operators. - Quan Sun; Bernhard Pfahringer; Michael Mayo (GECCO (Companion), 2012)

Batch-Incremental versus Instance-Incremental Learning in Dynamic and Evolving Data. - Jesse Read; Albert Bifet; Bernhard Pfahringer; Geoff Holmes 001 (IDA, 2012)

Maximum Common Subgraph based locally weighted regression. - Madeleine Seeland; Fabian Buchwald; Stefan Kramer 001; Bernhard Pfahringer (SAC, 2012)

Multi-label classification using boolean matrix decomposition. - Jörg Wicker; Bernhard Pfahringer; Stefan Kramer 001 (SAC, 2012)

Scalable and efficient multi-label classification for evolving data streams. - Jesse Read; Albert Bifet; Geoff Holmes 001; Bernhard Pfahringer (Mach. Learn., 2012)

Experiment databases - A new way to share, organize and learn from experiments. - Joaquin Vanschoren; Hendrik Blockeel; Bernhard Pfahringer; Geoffrey Holmes 001 (Mach. Learn., 2012)

Ensembles of Restricted Hoeffding Trees. - Albert Bifet; Eibe Frank; Geoff Holmes 001; Bernhard Pfahringer (ACM Trans. Intell. Syst. Technol., 2012)

Propositionalisation of Multi-instance Data Using Random Forests. - Eibe Frank; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2013)

The MOA Data Stream Mining Tool: A Mid-Term Report. - Bernhard Pfahringer (MLSDA@AUS-AI, 2013)

Clustering Based Active Learning for Evolving Data Streams. - Dino Ienco; Albert Bifet; Indre Zliobaite; Bernhard Pfahringer (Discovery Science, 2013)

SMOTE for Regression. - Luís Torgo; Rita P. Ribeiro; Bernhard Pfahringer; Paula Branco (EPIA, 2013)

CD-MOA: Change Detection Framework for Massive Online Analysis. - Albert Bifet; Jesse Read; Bernhard Pfahringer; Geoff Holmes 001; Indre Zliobaite (IDA, 2013)

A Direct Policy-Search Algorithm for Relational Reinforcement Learning. - Samuel Sarjant; Bernhard Pfahringer; Kurt Driessens; Tony Smith (ILP, 2013)

Towards a Framework for Designing Full Model Selection and Optimization Systems. - Quan Sun; Bernhard Pfahringer; Michael Mayo (MCS, 2013)

Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them. - Albert Bifet; Jesse Read; Indre Zliobaite; Bernhard Pfahringer; Geoff Holmes 001 (ECML/PKDD (1), 2013)

Efficient data stream classification via probabilistic adaptive windows. - Albert Bifet; Bernhard Pfahringer; Jesse Read; Geoff Holmes 001 (SAC, 2013)

Model selection based product kernel learning for regression on graphs. - Madeleine Seeland; Stefan Kramer 001; Bernhard Pfahringer (SAC, 2013)

Pairwise meta-rules for better meta-learning-based algorithm ranking. - Quan Sun; Bernhard Pfahringer (Mach. Learn., 2013)

Algorithm Selection on Data Streams. - Jan N. van Rijn; Geoffrey Holmes 001; Bernhard Pfahringer; Joaquin Vanschoren (Discovery Science, 2014)

Towards Meta-learning over Data Streams. - Jan N. van Rijn; Geoffrey Holmes 001; Bernhard Pfahringer; Joaquin Vanschoren (MetaSel@ECAI, 2014)

Détection de changements dans des flots de données qualitatives. - Dino Ienco; Albert Bifet; Bernhard Pfahringer; Pascal Poncelet (EGC, 2014)

High density-focused uncertainty sampling for active learning over evolving stream data. - Dino Ienco; Indre Zliobaite; Bernhard Pfahringer (BigMine, 2014)

Hierarchical Meta-Rules for Scalable Meta-Learning. - Quan Sun; Bernhard Pfahringer (PRICAI, 2014)

Change detection in categorical evolving data streams. - Dino Ienco; Albert Bifet; Bernhard Pfahringer; Pascal Poncelet (SAC, 2014)

Pruning Incremental Linear Model Trees with Approximate Lookahead. - Andreas Hapfelmeier; Bernhard Pfahringer; Stefan Kramer 001 (IEEE Trans. Knowl. Data Eng., 2014)

Active Learning With Drifting Streaming Data. - Indre Zliobaite; Albert Bifet; Bernhard Pfahringer; Geoffrey Holmes 001 (IEEE Trans. Neural Networks Learn. Syst., 2014)

Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams. - Jan N. van Rijn; Geoffrey Holmes 001; Bernhard Pfahringer; Joaquin Vanschoren (ICDM, 2015)

Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-Annotated Tweets. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (IJCAI, 2015)

Use of ensembles of Fourier spectra in capturing recurrent concepts in data streams. - Sripirakas Sakthithasan; Russel Pears; Albert Bifet; Bernhard Pfahringer (IJCNN, 2015)

Efficient Online Evaluation of Big Data Stream Classifiers. - Albert Bifet; Gianmarco De Francisci Morales; Jesse Read; Geoff Holmes 001; Bernhard Pfahringer (KDD, 2015)

On a Few Recent Developments in Meta-Learning for Algorithm Ranking and Selection. - Bernhard Pfahringer (MetaSel@PKDD/ECML, 2015)

From Unlabelled Tweets to Twitter-specific Opinion Words. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (SIGIR, 2015)

Learning Similarity Metrics by Factorising Adjacency Matrices. - Henry Gouk; Bernhard Pfahringer; Michael J. Cree (CoRR, 2015)

Bound Analysis for Whiley Programs. - Min-Hsien Weng; Mark Utting; Bernhard Pfahringer (USE@FM, 2015)

Resampling strategies for regression. - Luís Torgo; Paula Branco; Rita P. Ribeiro; Bernhard Pfahringer (Expert Syst. J. Knowl. Eng., 2015)

Evaluation methods and decision theory for classification of streaming data with temporal dependence. - Indre Zliobaite; Albert Bifet; Jesse Read; Bernhard Pfahringer; Geoff Holmes 001 (Mach. Learn., 2015)

Learning Distance Metrics for Multi-Label Classification. - Henry Gouk; Bernhard Pfahringer; Michael J. Cree (ACML, 2016)

Annotate-Sample-Average (ASA): A New Distant Supervision Approach for Twitter Sentiment Analysis. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (ECAI, 2016)

On Dynamic Feature Weighting for Feature Drifting Data Streams. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck; Bernhard Pfahringer; Albert Bifet (ECML/PKDD (2), 2016)

Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection. - Tim Leathart; Bernhard Pfahringer; Eibe Frank (ECML/PKDD (2), 2016)

Determining Word-Emotion Associations from Tweets by Multi-label Classification. - Felipe Bravo-Marquez; Eibe Frank; Saif M. Mohammad; Bernhard Pfahringer (WI, 2016)

From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (WI, 2016)

MEKA: A Multi-label/Multi-target Extension to WEKA. - Jesse Read; Peter Reutemann; Bernhard Pfahringer; Geoff Holmes 001 (J. Mach. Learn. Res., 2016)

Building a Twitter opinion lexicon from automatically-annotated tweets. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (Knowl. Based Syst., 2016)

Probability Calibration Trees. - Tim Leathart; Eibe Frank; Geoffrey Holmes 001; Bernhard Pfahringer (ACML, 2017)

Static techniques for reducing memory usage in the C implementation of whiley programs. - Min-Hsien Weng; Bernhard Pfahringer; Mark Utting (ACSW, 2017)

Learning Through Utility Optimization in Regression Tasks. - Paula Branco; Luís Torgo; Rita P. Ribeiro; Eibe Frank; Bernhard Pfahringer; Markus Michael Rau (DSAA, 2017)

Dynamic and Heterogeneous Ensembles for Time Series Forecasting. - Vítor Cerqueira; Luís Torgo; Mariana Oliveira 001; Bernhard Pfahringer (DSAA, 2017)

Extremely Fast Decision Tree Mining for Evolving Data Streams. - Albert Bifet; Jiajin Zhang; Wei Fan 001; Cheng He; Jianfeng Zhang; Jianfeng Qian; Geoff Holmes 001; Bernhard Pfahringer (KDD, 2017)

A survey on feature drift adaptation: Definition, benchmark, challenges and future directions. - Jean Paul Barddal; Heitor Murilo Gomes; Fabrício Enembreck; Bernhard Pfahringer (J. Syst. Softw., 2017)

Adaptive random forests for evolving data stream classification. - Heitor Murilo Gomes; Albert Bifet; Jesse Read; Jean Paul Barddal; Fabrício Enembreck; Bernhard Pfahringer; Geoff Holmes 001; Talel Abdessalem (Mach. Learn., 2017)

Conjunctive Normal Form. - Bernhard Pfahringer (Encyclopedia of Machine Learning and Data Mining, 2017)

Disjunctive Normal Form. - Bernhard Pfahringer (Encyclopedia of Machine Learning and Data Mining, 2017)

Combining active learning with concept drift detection for data stream mining. - Bartosz Krawczyk; Bernhard Pfahringer; Michal Wozniak 001 (IEEE BigData, 2018)

Deep Holistic Representation Learning from EHR. - Edmond Zhang; Reece Robinson; Bernhard Pfahringer (ISMICT, 2018)

MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. - Henry Gouk; Bernhard Pfahringer; Eibe Frank; Michael J. Cree (ECML/PKDD (1), 2018)

Using Supervised Pretraining to Improve Generalization of Neural Networks on Binary Classification Problems. - Alex Yuxuan Peng; Yun Sing Koh; Patricia Riddle; Bernhard Pfahringer (ECML/PKDD (1), 2018)

Iterative subset selection for feature drifting data streams. - Lanqin Yuan; Bernhard Pfahringer; Jean Paul Barddal (SAC, 2018)

On the Calibration of Nested Dichotomies for Large Multiclass Tasks. - Tim Leathart; Eibe Frank; Bernhard Pfahringer; Geoffrey Holmes 001 (CoRR, 2018)

A survey of automatic de-identification of longitudinal clinical narratives. - Vithya Yogarajan; Michael Mayo; Bernhard Pfahringer (CoRR, 2018)

The online performance estimation framework: heterogeneous ensemble learning for data streams. - Jan N. van Rijn; Geoffrey Holmes 001; Bernhard Pfahringer; Joaquin Vanschoren (Mach. Learn., 2018)

Transferring sentiment knowledge between words and tweets. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer (Web Intell., 2018)

Stochastic Gradient Trees. - Henry Gouk; Bernhard Pfahringer; Eibe Frank (ACML, 2019)

Investigating the effect of novel classes in semi-supervised learning. - Alex Yuxuan Peng; Yun Sing Koh; Patricia Riddle; Bernhard Pfahringer (ACML, 2019)

Semi-supervised Learning Using Siamese Networks. - Attaullah Sahito; Eibe Frank; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2019)

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams. - Heitor Murilo Gomes; Rodrigo Fernandes de Mello; Bernhard Pfahringer; Albert Bifet (IEEE BigData, 2019)

XOR-Based Boolean Matrix Decomposition. - Jörg Wicker; Yan Cathy Hua; Rayner Rebello; Bernhard Pfahringer (ICDM, 2019)

On Calibration of Nested Dichotomies. - Tim Leathart; Eibe Frank; Bernhard Pfahringer; Geoffrey Holmes 001 (PAKDD (1), 2019)

Ensembles of Nested Dichotomies with Multiple Subset Evaluation. - Tim Leathart; Eibe Frank; Bernhard Pfahringer; Geoffrey Holmes 001 (PAKDD (1), 2019)

Towards Automated Configuration of Stream Clustering Algorithms. - Matthias Carnein; Heike Trautmann; Albert Bifet; Bernhard Pfahringer (PKDD/ECML Workshops (1), 2019)

An ELMo-inspired approach to SemDeep-5's Word-in-Context task. - Alan Ansell; Felipe Bravo-Marquez; Bernhard Pfahringer (SemDeep@IJCAI, 2019)

Automatic end-to-end De-identification: Is high accuracy the only metric? - Vithya Yogarajan; Bernhard Pfahringer; Michael Mayo (CoRR, 2019)

Merit-guided dynamic feature selection filter for data streams. - Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (Expert Syst. Appl., 2019)

Boosting decision stumps for dynamic feature selection on data streams. - Jean Paul Barddal; Fabrício Enembreck; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (Inf. Syst., 2019)

AffectiveTweets: a Weka Package for Analyzing Affect in Tweets. - Felipe Bravo-Marquez; Eibe Frank; Bernhard Pfahringer; Saif M. Mohammad (J. Mach. Learn. Res., 2019)

Correction to: Adaptive random forests for evolving data stream classification. - Heitor Murilo Gomes; Albert Bifet; Jesse Read; Jean Paul Barddal; Fabrício Enembreck; Bernhard Pfahringer; Geoff Holmes 001; Talel Abdessalem (Mach. Learn., 2019)

Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes. - Vithya Yogarajan; Henry Gouk; Tony Smith; Michael Mayo; Bernhard Pfahringer (ACIIDS (1), 2020)

Transfer of Pretrained Model Weights Substantially Improves Semi-supervised Image Classification. - Attaullah Sahito; Eibe Frank; Bernhard Pfahringer (Australasian Conference on Artificial Intelligence, 2020)

A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. - Hongyu Wang 008; Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael Mayo (Australasian Conference on Artificial Intelligence, 2020)

C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. - Alessio Bernardo; Heitor Murilo Gomes; Jacob Montiel; Bernhard Pfahringer; Albert Bifet; Emanuele Della Valle (IEEE BigData, 2020)

Improving parallel performance of ensemble learners for streaming data through data locality with mini-batching. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (HPCC/DSS/SmartCity, 2020)

Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams. - Maroua Bahri; Bernhard Pfahringer; Albert Bifet; Silviu Maniu (IDA, 2020)

On Ensemble Techniques for Data Stream Regression. - Heitor Murilo Gomes; Jacob Montiel; Saulo Martiello Mastelini; Bernhard Pfahringer; Albert Bifet (IJCNN, 2020)

Adaptive XGBoost for Evolving Data Streams. - Jacob Montiel; Rory Mitchell; Eibe Frank; Bernhard Pfahringer; Talel Abdessalem; Albert Bifet (IJCNN, 2020)

confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms. - Matthias Carnein; Heike Trautmann; Albert Bifet; Bernhard Pfahringer (LION, 2020)

A review of Automatic end-to-end De-Identification: Is High Accuracy the Only Metric? - Vithya Yogarajan; Bernhard Pfahringer; Michael Mayo (Appl. Artif. Intell., 2020)

Seeing The Whole Patient: Using Multi-Label Medical Text Classification Techniques to Enhance Predictions of Medical Codes. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (CoRR, 2020)

An empirical analysis of binary transformation strategies and base algorithms for multi-label learning. - Adriano Rivolli; Jesse Read; Carlos Soares; Bernhard Pfahringer; André C. P. L. F. de Carvalho (Mach. Learn., 2020)

Transformers for Multi-label Classification of Medical Text: An Empirical Comparison. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (AIME, 2021)

Combining Static and Dynamic Analysis to Improve Machine Learning-based Malware Classification. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes (DSAA, 2021)

PolyLM: Learning about Polysemy through Language Modeling. - Alan Ansell; Felipe Bravo-Marquez; Bernhard Pfahringer (EACL, 2021)

Fast and lightweight binary and multi-branch Hoeffding Tree Regressors. - Saulo Martiello Mastelini; Jacob Montiel; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; André C. P. L. F. de Carvalho (ICDM (Workshops), 2021)

Studying and Exploiting the Relationship Between Model Accuracy and Explanation Quality. - Yunzhe Jia; Eibe Frank; Bernhard Pfahringer; Albert Bifet; Nick Jin Sean Lim (ECML/PKDD (2), 2021)

Improving Predictions of Tail-end Labels using Concatenated BioMed-Transformers for Long Medical Documents. - Vithya Yogarajan; Bernhard Pfahringer; Tony Smith; Jacob Montiel (CoRR, 2021)

Improving the performance of bagging ensembles for data streams through mini-batching. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (Inf. Sci., 2021)

Classifier Chains: A Review and Perspectives. - Jesse Read; Bernhard Pfahringer; Geoff Holmes 001; Eibe Frank (J. Artif. Intell. Res., 2021)

Regularisation of neural networks by enforcing Lipschitz continuity. - Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael J. Cree (Mach. Learn., 2021)

Multiclass Malware Classification Using Either Static Opcodes or Dynamic API Calls. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes; Vithya Yogarajan (AI, 2022)

Better Self-training for Image Classification Through Self-supervision. - Attaullah Sahito; Eibe Frank; Bernhard Pfahringer (AI, 2022)

Predicting COVID-19 Patient Shielding: A Comprehensive Study. - Vithya Yogarajan; Jacob Montiel; Tony Smith; Bernhard Pfahringer (AI, 2022)

Adaptive Neural Networks for Online Domain Incremental Continual Learning. - Nuwan Gunasekara; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (DS, 2022)

Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. - Hongyu Wang 008; Huon Fraser; Henry Gouk; Eibe Frank; Bernhard Pfahringer; Michael Mayo; Geoff Holmes 001 (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

A Comparison of Neural Network Architectures for Malware Classification Based on Noriben Operation Sequences. - Rajchada Chanajitt; Bernhard Pfahringer; Heitor Murilo Gomes (ICANN (1), 2022)

Adaptive Online Domain Incremental Continual Learning. - Nuwan Gunasekara; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (ICANN (1), 2022)

Concatenating BioMed-Transformers to Tackle Long Medical Documents and to Improve the Prediction of Tail-End Labels. - Vithya Yogarajan; Bernhard Pfahringer; Tony Smith; Jacob Montiel (ICANN (2), 2022)

Online Hyperparameter Optimization for Streaming Neural Networks. - Nuwan Gunasekara; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (IJCNN, 2022)

Alzheimer's Disease Detection via a Surrogate Brain Age Prediction Task using 3D Convolutional Neural Networks. - Chen Zheng; Bernhard Pfahringer; Michael Mayo (IJCNN, 2022)

A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal. - Yaqian Zhang; Bernhard Pfahringer; Eibe Frank; Albert Bifet; Nick Jin Sean Lim; Yunzhe Jia (NeurIPS, 2022)

Incremental Word Vectors for Time-Evolving Sentiment Lexicon Induction. - Felipe Bravo-Marquez; Arun Khanchandani; Bernhard Pfahringer (Cogn. Comput., 2022)

Cross-domain Few-shot Meta-learning Using Stacking. - Hongyu Wang 008; Eibe Frank; Bernhard Pfahringer; Michael Mayo; Geoffrey Holmes 001 (CoRR, 2022)

SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams. - Yibin Sun; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (Data Min. Knowl. Discov., 2022)

LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding. - Emanuele Pio Barracchia; Gianvito Pio; Albert Bifet; Heitor Murilo Gomes; Bernhard Pfahringer; Michelangelo Ceci (Inf. Sci., 2022)

Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. - Anton Lee; Yaqian Zhang; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer (CIKM, 2023)

Self-trained Centroid Classifiers for Semi-supervised Cross-domain Few-shot Learning. - Hongyu Wang 008; Eibe Frank; Bernhard Pfahringer; Geoffrey Holmes 001 (CoLLAs, 2023)

Survey on Online Streaming Continual Learning. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (IJCAI, 2023)

Large scale K-means clustering using GPUs. - Mi Li; Eibe Frank; Bernhard Pfahringer (Data Min. Knowl. Discov., 2023)

Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computing. - Guilherme Weigert Cassales; Heitor Murilo Gomes; Albert Bifet; Bernhard Pfahringer; Hermes Senger (IEEE Trans. Netw. Serv. Manag., 2023)

teex: A toolbox for the evaluation of explanations. - Jesus Antonanzas; Yunzhe Jia; Eibe Frank; Albert Bifet; Bernhard Pfahringer (Neurocomputing, 2023)

ASML: A Scalable and Efficient AutoML Solution for Data Streams. - Nilesh Verma; Albert Bifet; Bernhard Pfahringer; Maroua Bahri (AutoML, 2024)

Mini-batching with Fused Training and Testing for Data Streams Processing on the Edge. - Reginaldo Luna; Guilherme Weigert Cassales; Bernhard Pfahringer; Albert Bifet; Heitor Murilo Gomes; Hermes Senger (CF, 2024)

Online Isolation Forest. - Filippo Leveni; Guilherme Weigert Cassales; Bernhard Pfahringer; Albert Bifet; Giacomo Boracchi (ICML, 2024)

Enhanced Stance Detection Using Cascaded Siamese Networks with Attention Mechanism. - Muhammad Zain Ali; Tony C. Smith; Bernhard Pfahringer (ICONIP (9), 2024)

Recurrent Concept Drifts on Data Streams. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet; Yun Sing Koh (IJCAI, 2024)

Time-Evolving Data Science and Artificial Intelligence for Advanced Open Environmental Science (TAIAO) Programme. - Yun Sing Koh; Albert Bifet; Karin R. Bryan; Guilherme Weigert Cassales; Olivier Graffeuille; Nick Jin Sean Lim; Phil Mourot; Ding Ning; Bernhard Pfahringer; Varvara Vetrova; Heitor Murilo Gomes (IJCAI, 2024)

Adaptive Prediction Interval for Data Stream Regression. - Yibin Sun; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (PAKDD (3), 2024)

Leveraging Plasticity in Incremental Decision Trees. - Marco Heyden; Heitor Murilo Gomes; Edouard Fouché; Bernhard Pfahringer; Klemens Böhm (ECML/PKDD (5), 2024)

Real-Time Energy Pricing in New Zealand: An Evolving Stream Analysis. - Yibin Sun; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (PRICAI (5), 2024)

Optimizing Hyperparameters for Quantum Data Re-Uploaders in Calorimetric Particle Identification. - Léa Cassé; Bernhard Pfahringer; Albert Bifet; Frédéric Magniette (CoRR, 2024)

Machine Learning (In) Security: A Stream of Problems. - Fabrício Ceschin; Marcus Botacin; Albert Bifet; Bernhard Pfahringer; Luiz S. Oliveira; Heitor Murilo Gomes; André Grégio (DTRAP, 2024)

Feature extractor stacking for cross-domain few-shot learning. - Hongyu Wang 008; Eibe Frank; Bernhard Pfahringer; Michael Mayo; Geoff Holmes 001 (Mach. Learn., 2024)

Gradient boosted trees for evolving data streams. - Nuwan Gunasekara; Bernhard Pfahringer; Heitor Murilo Gomes; Albert Bifet (Mach. Learn., 2024)

Detection of Human and Machine-Authored Fake News in Urdu. - Muhammad Zain Ali; Yuxia Wang; Bernhard Pfahringer; Tony C. Smith (ACL (1), 2025)

Streaming Isolation Forest. - Justin Jia Liu; Guilherme Weigert Cassales; Fei Tony Liu; Bernhard Pfahringer; Albert Bifet (PAKDD (1), 2025)

Auto-Reg: A Dynamic AutoML Framework for Streaming Regression. - Nilesh Verma; Albert Bifet; Bernhard Pfahringer; Maroua Bahri (PAKDD (4), 2025)

ASML-REG: Automated Machine Learning for Data Stream Regression. - Nilesh Verma; Albert Bifet; Bernhard Pfahringer; Maroua Bahri (SAC, 2025)

A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study. - Guilherme Weigert Cassales; Serajis Salekin; Nick Jin Sean Lim; Dean F. Meason; Albert Bifet; Bernhard Pfahringer; Eibe Frank (Ecol. Informatics, 2025)

Pruning Feature Extractor Stacking for Cross-domain Few-shot Learning. - Hongyu Wang 008; Eibe Frank; Bernhard Pfahringer; Geoff Holmes 001 (Trans. Mach. Learn. Res., 2025)

Evaluation for Regression Analyses on Evolving Data Streams. - Yibin Sun; Heitor Murilo Gomes; Bernhard Pfahringer; Albert Bifet (CoRR, 2025)

CapyMOA: Efficient Machine Learning for Data Streams in Python. - Heitor Murilo Gomes; Anton Lee; Nuwan Gunasekara; Yibin Sun; Guilherme Weigert Cassales; Justin Liu; Marco Heyden; Vítor Cerqueira; Maroua Bahri; Yun Sing Koh; Bernhard Pfahringer; Albert Bifet (CoRR, 2025)

Ai-enabled automated common vulnerability scoring from common vulnerabilities and exposures descriptions. - Zijing Zhang; Vimal Kumar 001; Bernhard Pfahringer; Albert Bifet (Int. J. Inf. Sec., 2025)